A unified analysis of atlas single cell data

Abstract

Recent efforts to generate atlas-scale single-cell data provide opportunities for joint analysis across tissues and modalities. Existing methods use cells as the reference unit, hindering downstream gene-based analysis and removing genuine biological variations. Here we present GIANT, an integration method designed for atlas-scale gene analysis across cell types and tissues. GIANT converts datasets into gene graphs and recursively embeds genes without additional alignment. Applying GIANT to two recent atlas datasets yields unified gene embedding spaces across human tissues and data modalities. Further evaluations demonstrate GIANT's usefulness in discovering diverse gene functions and underlying gene regulations in cells from different tissues.